import tensorflow as tf
import numpy as np


# 创建数据
x_data = np.random.rand(100).astype(np.float32)
y_data = x_data*0.1+0.3

# 创建一个tensorflow图

Weights = tf.Variable(tf.random_uniform([1],-1.0,1.0))
Biases = tf.Variable(tf.zeros([1]))

y = Weights*x_data+Biases

loss = tf.reduce_mean(tf.square(y-y_data))

optimizer = tf.train.GradientDescentOptimizer(0.5)

train = optimizer.minimize(loss)

# 初始化变量----创建这个图
init = tf.initialize_all_variables()

# 将图激活
sess = tf.Session()
sess.run(init)  # very importance
# 创建一个tensorflow图

for step in range(201):
    sess.run(train)
    if step % 20 == 0:
        print(step,sess.run(Weights),sess.run(Biases))
